Author/Editor		Kokol, P; Završnik, J; Zorman, M; Malčič, I; Kancler, K
Title		Participative design, decision trees, automatic learning and medical decision making
Type		članek
Source		In: Brender J, Christensen JP, Scherrer JR, et al, editors. MIE 96. Medical informatics Europe '96. (Part A,B): human factes in information technologies. Tokyo: IOS Press,
Publication year		1996
Volume		str. 501-5
Language		eng
Abstract		Decision support system (DSS) have become increasingly important in medical applications, particulary when important decision must be made effectively and reliably. The best way to design a successful DSS is trough the parcitipative design, thereafter conceptual simple decision marking models with the possiblity of automating learning should be considered in the design phase and then implemented by conceptual simple paradigms. In this paper we present a cardiological decision support system, called RO2SE (computeRised PrOlaps Syndrome dEtermination, O2 stands for Objekt Oriented implementation), based on decision tree approach and automatic learning, supporting the proces of mitral valve prolapse determination. RO2SE is implemented using Objekt Orientedvisual programming language.
Descriptors		DECISION MAKING, COMPUTER-ASSISTED MITRAL VALVE PROLAPSE DECISION SUPPORT TECHNIQUES